Statistical Analysis in the Safety Evaluation of Genetically-Modified Crops: Equivalence Tests

摘要

Risk assessment is an important step in the process of deregulating a genetically modified (GM) crop and its derived products for food and feed. The European Food Safety Authority (EFSA) evaluates safety by testing for the average equivalence between the GM crop and a group of commercial non-GM reference varieties representing a population of crops with a history of safe use. This paper defines the equivalence tests described by EFSA in terms of parameters in the mixed model. A basic strategy for the equivalence tests is proposed. Generalized inference is employed to overcome two challenges in testing equivalences: the unconventional parameter of interest and the limited number of reference varieties. Balanced or partially balanced incomplete designs are recommended in equivalence testing. Simulation indicates this new method maintains the desired type I error rate and holds good power under practical designs. An illustrative data example is used to demonstrate the execution of the proposed method in SAS. Finally, issues associated with the equivalence tests and suggested topics for future research are discussed.